Constraint Shortest Path Problem Research Articles

Telesurgery QoS improvement over SDN based on a Type‐2 fuzzy system and enhanced cuckoo optimization algorithm

SummaryTelemedicine is a new area based on the information and communication technology for collecting, storing, organizing, retrieving and exchanging medical information. One of the most important applications of telemedicine is indeed telesurgery in which an efficient telecommunication infrastructure between the surgery room and remote surgeons need to be established. One of the most important issues to be tackled in telesurgery is to find favorable links for routing as well as providing high Quality of Service (QoS). In this paper, an efficient model based on the hybridization of Type‐2 Fuzzy System (T2FS) and Cuckoo Optimization Algorithm (COA) over the Software Defined Networks (SDN) is proposed in order to achieve optimal and reliable routes for telesurgery application. Using T2FS, the fitness of the links is determined; then, a COA is conducted over the Constraint Shortest Path (CSP) problem to find the best routes. Delay is considered as a CSP problem which is satisfied by trying to find the paths with minimum cost. Due to the NP‐completeness of the CSP problem, an Enhanced COA (so‐called E‐COA) is proposed and utilized as a metaheuristic solver. To the best of our knowledge, this paper is the first SDN‐based communication model that applies both T2FS and E‐COA for assigning proper costs to the network's links, and solves the consequence CSP problem according to the QoS requirement for telesurgery. The model also recognizes and preserves the second‐best routes in order to keep the reliability for such a critical application. In addition to the simulations, the performance evaluation is also conducted on a real experimental scenario. Many comparisons are carried out between the proposed model and other conventional methods, and the evaluation study shows the superiority of the proposed model on all the three QoS‐related metrics, i.e. average end‐to‐end delay, packet loss ratio and PSNR.

A new adaptive traffic engineering method for telesurgery using ACO algorithm over Software Defined Networks

Summary Introduction In the past decades, telemedicine has attracted much attention due to its usefulness for delivering medical services from remote location. One of the most important parts of telemedicine is telesurgery, in which a surgeon performs surgery on the patient from remote location by using telecommunication networks. Due to the surgeon needs to watch the patient side transmitted video with high quality; it is necessary to provide fast and suitable communication path between the surgeon and patient. Emerging Software Defined Network (SDN) as a new network paradigm facilitated Quality of Service (QoS) provisioning in many applications. Decoupling data plane from control plane in SDN, helps to manage based on end users requirements. This paper proposes a new heuristic traffic engineering method for telesurgery application using Ant Colony Optimization (ACO) algorithm. Patients and methods This paper models QoS provisioning in Telesurgery as a Constraint Shortest Path (CSP) linear programming problem. Moreover, due to NP-completeness of CSP problem, this paper proposes a solver method using ACO algorithm. To the best of our knowledge, this is the first paper which investigates QoS provisioning for telesurgery in SDN. Results Results of performance evaluation showed that the proposed method is better than baseline method. The proposed method improves all three important QoS parameters, average End-to-End delay, packet loss ratio and PSNR with values of 56.3%, 50.5% and 1.33, respectively. Discussion providing QoS in telesurgery applications is one of the most challenging issues. By leveraging the capability of SDN, we can develop appropriate mechanisms to guarantee QoS requirements in critical applications such as Telesurgery. Conclusion Using SDN together with optimization models such as CSP for providing QoS in Telesurgery can improve the quality of the received video in an operation room. This mechanism causes increment in the performance of Telesurgery.

An Intelligent Traffic Engineering Method over Software Defined Networks for Video Surveillance Systems Based on Artificial Bee Colony

In applications such as video surveillance systems, cameras transmit video data streams through network in which quality of received video should be assured. Traditional IP based networks cannot guarantee the required Quality of Service (QoS) for such applications. Nowadays, Software Defined Network (SDN) is a popular technology, which assists network management using computer programs. In this paper, a new SDN-based video surveillance system infrastructure is proposed to apply desire traffic engineering for practical video surveillance applications. To keep the quality of received videos adaptively, usually Constraint Shortest Path (CSP) problem is used which is a NP-complete problem. Hence, heuristic algorithms are suitable candidate for solving such problem. This paper models streaming video data on a surveillance system as a CSP problem, and proposes an artificial bee colony (ABC) algorithm to find optimal solution to manage the network adaptively and guarantee the required QoS. The simulation results show the effectiveness of the proposed method in terms of QoS metrics.